Process simulations can lead to varieties of advantages (safety, prediction and control of the process, scaling, etc.). However, for simulations reliability, the model must be consistent to the observed experimental data, which it must predict as accurate as possible. Besides, good parameter estimation is needed in order to adjust the model to the process. These parameters usually cannot be measured, so they need to be estimated from available experimental data through minimization of some objective function. The goal of this study is to estimate the parameters of the ODEs of a solid-state fermentation (SSF) process and analyze the system behavior before some parameters changes. The model is composed of 6 ODEs that contain the cells profile, its physiological state, temperature, substrate consumption and product, CO2 and O2 production by the cells metabolism. SSF is a fermentation process with no free water (substrate must contain only enough moisture to support microorganisms growth).